Business Intelligence Data Architect

Contentstack; Portugal; On-site; EUR 90,000 - 130,000; Full time

Job summary

Contentstack is seeking a BI Data Architect to shape the analytical architecture, data modeling standards, and engineering practices powering enterprise reporting and AI-enabled analytics.

You will establish scalable modeling frameworks across Snowflake and dbt, lead governance, and partner with Data Engineering, BI & Analytics, Revenue Operations, and Finance to build a trusted data foundation for data-driven decision-making.

Qualifications

• 5-8 years of experience in data engineering, analytics engineering or data architecture.
• At least 3 years in an architect capacity with direct ownership of an analytical platform.
• Deep hands-on expertise in Snowflake architecture and dbt.

Responsibilities

• Define enterprise modeling standards across staging, intermediate, dimensional, fact, semantic, and mart layers.
• Design and implement reusable business entities, semantic models, and enterprise metrics for reporting and AI-enabled workflows.
• Set standards for dbt development, testing, Git workflows, CI/CD, deployment reliability, model performance and observability.
• Design governed access patterns for applications, AI agents, and self-service tools consuming Snowflake data (RBAC).
• Collaborate with Data Engineering, BI & Analytics, Revenue Operations and Finance to translate business requirements into scalable data models.
• Mentor analytics engineers on modular architecture and reusable modeling patterns.

Skills

Snowflake architecture

dbt

RBAC

Semantic modeling

Dimensional modeling

Jinja macros

Incremental models

Analytical platform

Data engineering

Tools

Snowflake

dbt

Git

Job description

What is Contentstack ?

Contentstack is redefining how modern digital experiences are built and managed. As the pioneer of the Agentic Experience Platform (AXP), Contentstack brings together structured content and brand governance (Content Cloud), real-time customer data, omnichannel personalization (Data Cloud) and autonomous AI orchestration (Agent OS) into one unified system.

While many organizations adopted headless CMS or standalone AI tools expecting transformation, they often found themselves managing disconnected systems and manual workflows. Contentstack helps enterprises move beyond that complexity by connecting content, data and AI in a way that makes digital experiences faster to launch, easier to manage and more adaptive in real time.

Leading brands including Steve Madden, LG Electronics, Subaru of America, Dolce & Gabbana, ASICS, Decathlon, and Caesars Entertainment rely on Contentstack to reduce operational friction and deliver personalized, scalable digital experiences with confidence. The company is known for its customer-first culture and commitment to the communities it serves through the Contentstack Cares program.

Learn more at www.contentstack.com .

Who Are We?

At Contentstack we are more than colleagues, we are a tribe. Our vision is to pursue equity among our communities, employees, partners, and customers. We are global-diverse yet close; distributed yet connected. We are dreamers and dreammakers who challenge the status quo. We do the right thing, even when no one is watching. We are curious trendspotters and brave trendsetters. Our mission is to make Contentstack indispensable for organizations to tell their stories and to connect with the people they care about through inspiring, modern experiences. We care deeply about our customers and the communities we serve. #OneTeamOneDream. Chalo, let's go!

What Are We Looking For?

We're looking for a Business Intelligence Data Architect to shape the analytical architecture, data modeling standards, and engineering practices that power enterprise reporting, governed metrics, and AI-enabled analytics at Contentstack.

In this high-impact role, you'll establish scalable, reusable modeling frameworks across Snowflake and dbt, lead the implementation of governed semantic models, and partner with Data Engineering, BI & Analytics, Revenue Operations, Finance, and executive leadership to build a trusted foundation for data-driven decision-making.

If you're passionate about modern analytics architecture, translating complex business needs into scalable solutions, and enabling the next generation of AI-powered analytics, we'd love to hear from you! Here's what you'll be doing:

Lead analytical architecture and governance: Define enterprise modeling standards across staging, intermediate, dimensional, fact, semantic, and mart layers. Establish conventions for model grain, naming, ownership, lineage, and documentation, and lead architectural design reviews.

Build governed data models and semantic layers: Design and implement reusable business entities, semantic models, and enterprise metrics that support consistent reporting, self-service analytics, applications, and AI-enabled workflows.

Establish analytics engineering best practices: Set standards for dbt development, testing, Git workflows, CI/CD, deployment reliability, model performance, and observability to improve scalability and maintainability.

Enable secure, reliable data access: Design governed access patterns for applications, AI agents, and self-service tools consuming Snowflake data, including role-based access control (RBAC), APIs, service layers, and query optimization.

Partner across the business: Work closely with Data Engineering, BI & Analytics, Revenue Operations, Finance, and executive stakeholders to translate business requirements into trustworthy data models and scalable analytics solutions.

Mentor and enable the team: Guide analytics engineers on modular architecture, semantic implementation, reusable modeling patterns, and modern analytics engineering practices.

Drive platform evolution: Evaluate tools, semantic technologies, governance capabilities, and architectural improvements that support long-term scalability while reducing technical debt.

5-8 years of experience in data engineering, analytics engineering, or data architecture, including at least 3 years in an architect capacity with direct ownership of an analytical platform. Deep, hands-on expertise in Snowflake architecture, including virtual warehouse design, RBAC, materialization strategies, dynamic tables, and query performance optimization. Expert-level experience with dbt, including staging/intermediate/mart conventions, Jinja macros, incremental models, testing, documentation, and reusable modeling patterns. Strong understanding of dimensional and semantic modeling, with the ability to selec

What Really Gets Us Excited About You